Daily Mean Values Research Articles

Comparison of plasma methionine response to 3 rumen-protected methionine products in lactating Holstein dairy cows

The primary aim of this work was to compare the plasma Met response to supplementation with 3 rumen-protected Met products. Secondary aims were to evaluate how time of sampling affected results and how pooling of samples may have affected results. Ten multiparous Holstein cows (280 ± 73 DIM) were used in a replicated 3 × 3 Latin square design with 7-d experimental periods. Cows were fed every 8 h, and treatments consisted of supplementation of 12 g/d (4 g/feeding) of 1 of 3 rumen-protected Met (RPM) products. The products evaluated were the newly developed RPM-K and 2 existing products, RPM-S and RPM-M, with known differences in bioavailability. During d 5 to 7 of each period, blood samples were collected at 2, 4, 6, and 8 h after the morning feeding for plasma free AA analysis. Plasma Met data were analyzed using the full data set as well as mean values from individual cows for each day or each period. Plasma Met was not different between RPM-S and RPM-K (32.7 vs. 33.0 μ M , respectively; P = 0.79), and both were greater than RPM-M (30.1 μ M ; P ≤ 0.001). Plasma Met was affected by time of sampling ( P = 0.001), due to reduced plasma Met at 4 h (30.2 μ M ) than at 2, 6, and 8 h (31.9–33.0 μ M ). Using the daily and period mean values of plasma Met, differences observed in the full model were maintained when daily means were evaluated, but period means resulted in only a tendency for a treatment effect. Bioavailability of RPM-K was similar to RPM-S and greater than RPM-M. Pooling samples by day within cow would have likely yielded similar results.

Climatology of Aerosols over the Caribbean Islands: Aerosol Types, Synoptic Patterns, and Transport

Abstract We present a climatological study of aerosols in four representative Caribbean Sea islands that is based on daily mean values of aerosol optical properties for the period 2008–16, using the aerosol optical depth (AOD) and Ångström exponent (AE) to classify the dominant aerosol type. A climatological assessment of the spatiotemporal distribution of the main aerosol types, their links with synoptic patterns, and the transport from different sources is provided. Maximum values of AOD occur in the rainy season, coinciding with the minimum in AE and an increased occurrence of dust, whereas the minimum of AOD occurs in the dry season, due to the predominance of marine aerosols. Marine and dust aerosol are more frequent in the easternmost islands and decrease westward because of an increase of continental and mixture dust aerosols. Therefore, the westernmost station displays the most heterogeneous composition of aerosols. Using a weather-type classification, we identify a quantifiable influence of the atmospheric circulation in the distribution of Caribbean aerosols. However, they can occur under relatively weak and/or diverse synoptic patterns, typically involving transient systems and specific configurations of the Azores high that depend on the considered station. Backward trajectories indicate that dry-season marine aerosols and rainy-season dust are transported by air parcels traveling within the tropical easterly winds. The main source region for both types of aerosols is the subtropical eastern Atlantic Ocean, except for Cuba, where the largest contributor to dry-season marine aerosols is the subtropical western Atlantic. Different aerosol types follow similar pathways, suggesting a key role of emission sources in determining the spatiotemporal distribution of Caribbean aerosols.

“On-Line” Heating Emissions Based on WRF Meteorology—Application and Evaluation of a Modeling System over Greece

The main objective of the present study is the development of an “on-line” heating emissions modeling system based on simulated meteorological data and its integration with air quality modeling systems in order to improve their accuracy. The WRF-CAMx air quality modeling system is applied over Greece for the cold period of 2015 (January–April, October–December) for two emissions scenarios: using the (a) “on-line” heating emissions based on WRF meteorology and (b) “static” heating emissions based on static temporal profiles. The monthly variation in total “on-line” heating emissions followed the temporal pattern of the air temperature over Greece, leading to the highest heating emissions in January and February, while higher differences in emissions between winter and spring/autumn months were identified in comparison with the static ones. The overall evaluation of the WRF-CAMx modeling system using the “on-line” heating emissions revealed satisfactory model performance for the mean daily air quality levels. The comparison between the simulated and observed mean monthly concentrations revealed an improvement in the pattern of mean monthly concentrations for the “on-line” scenario. Higher values of the index of agreement and correlation for the mean daily values were also identified for the “on-line” scenario in most monitoring sites.

Mount Everest's photogenic weather during the post‐monsoon

Mount Everest's photogenic weather during the post‐monsoon

Assessing the Potential of Downscaled Far Red Solar-Induced Chlorophyll Fluorescence from the Canopy to Leaf Level for Drought Monitoring in Winter Wheat

Solar-induced chlorophyll fluorescence (SIF) from ground, airborne, and satellite-based observations has been increasingly used in drought monitoring recently due to its close relationship with photosynthesis. SIF emissions respond rapidly to droughts, relative to the widely used vegetation indices (VIs), thus indicating their potential for early drought monitoring. The response of SIF to droughts can be attributed to the confounding effects of both the physiology and canopy structure. In order to reduce the reabsorption and scattering effects, the total emitted SIF (SIFtot) was proposed and served as a better tool to estimate GPP compared with the top-of-canopy SIF (SIFtoc). However, the response time and response magnitude of SIFtot to droughts and its relationships with the environmental parameters and soil moisture (SM) (i.e., the knowledge of drought monitoring using SIFtot) remains unclear. Here, the continuous ground data of F760toc (SIFtoc at 760 nm) from a nadir view that was downscaled to F760tot (SIFtot at 760 nm), NIRv, and the NDVI, SM, meteorological, and crop growth parameters were measured from four winter wheat plots with different intensities of drought (well-watered, moderate drought, severe drought, and extreme drought) over 2 months. The results indicated that F760tot was more closely correlated with the SM than the VIs at short time lags but weaker at longer time lags. The daily mean values of F760tot and NIRv were able to distinguish the differences between different drought levels, and F760tot responded quickly to the onset of drought, especially for the moderate drought intensity. These findings demonstrated that F760tot has potential for early drought monitoring and may contribute to mitigating the risk of agricultural drought.

Characterization of peroxyacetyl nitrate (PAN) under different PM2.5 concentration in wintertime at a North China rural site

As a secondary pollutant of photochemical pollution, peroxyacetyl nitrate (PAN) has attracted a close attention. A four-month campaign was conducted at a rural site in North China Plain (NCP) including the measurement of PAN, O3, NOx, PM2.5, oxygenated volatile organic compounds (OVOCs), photolysis rate constants of NO2 and O3 and meteorological parameters to investigate the wintertime characterization of photochemistry from November 2018 to February 2019. The results showed that the maximum and mean values of PAN were 4.38 and 0.93 ± 0.67 ppbv during the campaign, respectively. The PAN under different PM2.5 concentrations from below 75 μg/m3 up to 250 μg/m3, showed different diurnal variation and formation rate. In the PM2.5 concentration range of above 250 μg/m3, PAN had the largest daily mean value of 0.64 ppbv and the fastest production rate of 0.33 ppbv/hr. From the perspective of PAN's production mechanism, the light intensity and precursors concentrations under different PM2.5 pollution levels indicated that there were sufficient light intensity and high volatile organic compounds (VOCs) and NOx precursors concentration even under severe pollution level to generate a large amount of PAN. Moreover, the bimodal staggering phenomenon of PAN and PM2.5 provided a basis that PAN might aggravate haze through secondary organic aerosols (SOA) formation.

Burning urban cities of South Africa due to civil turmoil 2021: Socio-economic and environmental consequences

A violent outbreak of civil unrest (Jul 7–19, 2021) triggered immediately after the incarceration of the former South African president claimed 337 lives and brought disruptive damages to societal movements, environment, and COVID-19 containment measures. The present work aimed to analyze the hotspots of fire sites, its significances on societal activities, air quality and COVID-19 pandemic using ground based and geospatial data. The results revealed steady rise in air pollution levels all through the region due to increase in fire activities. Positive influence on the regional air quality was observed to be high than the limits set forth by WHO. The daily mean values of PM2.5 (62.37–104.34 μg/m3) and PM10 (108.86–156.78 μg/m3) presented potential short and long-term risks to public health. Similarly, COVID-19 cases also increased during the social unrest period even when the community mobility was less than the normal conditions. This type of cost benefit analysis proves to provide evidence of deteriorating air quality and aids to examine the adverse impacts on human health during the global pandemic.

Influence of weather conditions on Lobesia botrana (Lepidoptera: Tortricidae) mating disruption dispensers’ emission rates and efficacy

Passive dispensers are the most widely used dispensers to control the European grapevine moth, Lobesia botrana (Denis & Schiffermüller) (Lepidoptera: Tortricidae), by mating disruption (MD). Although their efficacy is well-proven, efforts are needed to reduce the use of pheromone without compromising efficacy and to allow lower MD costs. For this purpose, two different widely employed dispenser types in Europe against this pest (Ampoule and Rope dispensers) were evaluated in the field to verify their performance (emission rates and efficacy) in relation to weather conditions. Their release profiles were studied by extracting and quantifying the residual pheromone load over time by gas chromatography. Dispensers' performance in relation to weather conditions was then assessed by correlating the daily emission rates with the mean daily values of several of these variables. Although both dispenser types were efficient in controlling L. botrana populations and reducing fruit damage, their pheromone content and their release rates differed at the end of the crop cycle. The Ampoule dispensers emitted lower amounts of pheromone throughout the study period, whereas the Rope dispensers’ emissions were weather-dependent, with higher emission rates at higher mean temperatures and wind speeds. Our results showed that the current commercial MD dispensers could be improved by adjusting their release rates to better reflect actual pheromone requirements.

Effects of Rainfall on the Characteristics of Soil Greenhouse Gas Emissions in the Wetland of Qinghai Lake

Niaodao, a lakeside wetland, was used as the focus of this study to investigate the effect of rainfall changes on the greenhouse gas fluxes of wetland ecosystems. Wetland plots with different moisture characteristics (+25%, −25%, +75%, and −75% rainfall treatments and the control treatment (CK)) were constructed to observe in situ field greenhouse gas emissions at 11:00 and 15:00 (when the daily mean values were similar) in the growing season from May to August 2020 by static chamber–gas chromatography and to investigate the responses of wetland greenhouse gases to different rainfall treatments. The results showed the following: (1) The carbon dioxide (CO2) flux ranged from −49.409 to 374.548 mg·m−2·h−1. The mean CO2 emission flux was greater at 11:00 than at 15:00, and the +25% and +75% treatments exhibited substantially higher CO2 emissions. In addition, the CO2 flux showed a small peak at the beginning of the growing season when the temperature first started to rise. All treatments showed the effect of the CO2 source, and their effects were significantly different. (2) The methane (CH4) flux ranged from −213.839 to 330.976 µg·m−2·h−1 and exhibited an absorption state at 11:00 and an emission state at 15:00. The CH4 emission flux in August (the peak growing season) differed greatly between treatments and was significantly negatively correlated with the rainfall amount (p < 0.05). (3) The nitrous oxide (N2O) flux ranged from −10.457 to 16.878 µg·m−2·h−1 and exhibited a weak source effect throughout the growing season, but it was not significantly correlated with soil moisture; it was, however, negatively correlated with soil temperature. (4) The different treatments resulted in significant differences in soil physical and chemical properties (electrical conductivity, pH, total soil carbon, and total soil nitrogen). The rainfall enhancement treatments significantly improved soil physical and chemical properties.

On the Radiative Impact of Biomass-Burning Aerosols in the Arctic: The August 2017 Case Study

Boreal fires have increased during the last years and are projected to become more intense and frequent as a consequence of climate change. Wildfires produce a wide range of effects on the Arctic climate and ecosystem, and understanding these effects is crucial for predicting the future evolution of the Arctic region. This study focuses on the impact of the long-range transport of biomass-burning aerosol into the atmosphere and the corresponding radiative perturbation in the shortwave frequency range. As a case study, we investigate an intense biomass-burning (BB) event which took place in summer 2017 in Canada and subsequent northeastward transport of gases and particles in the plume leading to exceptionally high values (0.86) of Aerosol Optical Depth (AOD) at 500 nm measured in northwestern Greenland on 21 August 2017. This work characterizes the BB plume measured at the Thule High Arctic Atmospheric Observatory (THAAO; 76.53∘N, 68.74∘W) in August 2017 by assessing the associated shortwave aerosol direct radiative impact over the THAAO and extending this evaluation over the broader region (60∘N–80∘N, 110∘W–0∘E). The radiative transfer simulations with MODTRAN6.0 estimated an aerosol heating rate of up to 0.5 K/day in the upper aerosol layer (8–12 km). The direct aerosol radiative effect (ARE) vertical profile shows a maximum negative value of −45.4 Wm−2 for a 78∘ solar zenith angle above THAAO at 3 km altitude. A cumulative surface ARE of −127.5 TW is estimated to have occurred on 21 August 2017 over a portion (∼3.1×106 km2) of the considered domain (60∘N–80∘N, 110∘W–0∘E). ARE regional mean daily values over the same portion of the domain vary between −65 and −25 Wm−2. Although this is a limited temporal event, this effect can have significant influence on the Arctic radiative budget, especially in the anticipated scenario of increasing wildfires.

Magnitude, consequences and correction of temperature‐derived errors for absolute pressure transducers under common monitoring scenarios

AbstractContinuous water level monitoring using absolute pressure transducers with onboard data logging is common practice in hydrologic studies. While there has been some discussion and study of temperature‐derived error (TDE), there has not been a systematic evaluation of the problem. We sought to answer three questions: (1) are current best practices enough to avoid these errors, (2) can laboratory correction be used to correct field data from varying conditions, and (3) what is the scale of the additional uncertainty of the correction procedure? We evaluated the magnitude of such errors under laboratory conditions that mimicked common monitoring scenarios. Using field data, we also demonstrated the impact of TDEs on calculated daily mean water level and diurnal signal decomposition to estimate evapotranspiration (ET). To address instrument and model uncertainty, we fit 1000 possible correction models using a double‐bootstrap approach. Correction models fit expected error as a function of water and air temperature and rate of change of air temperature. TDEs were a significant source of error, resulting in recorded data outside of manufacturer‐stated instrument uncertainty, with 45% of bootstrap models showing significant but small TDEs under best‐practice deployment. Correction equations did introduce additional error, often on a much smaller scale than instrument uncertainty. When tested against a validation data set, correction equations effectively reduced total measurement uncertainty below instrument uncertainty by up to 65%. The effects of TDEs on case‐study field data resulted in 56% of daily mean values outside of instrument error bounds (errors: −1.5 to 4.2 cm). Our results suggest that a single laboratory correction equation can be used across monitoring scenarios, though we suggest matching deployment conditions as closely as practical. Identification and correction of TDEs is essential to avoid erroneous conclusions, downstream analyses and water resources management.

Chemical Composition and Source Apportionment of PM2.5 in a Border City in Southwest China

This paper studied the chemical characteristics and seasonal changes of PM2.5 in plateau cities on the southwest border of China. Urban air was sampled in Baoshan City during the rainy and dry seasons. Finally, 174 PM2.5 filters were collected (including 87 quartz and 87 Teflon samples for PM2.5). The mass concentrations, water-soluble inorganic ions, organic and inorganic carbon concentrations, and inorganic elements constituting PM2.5 were determined. Positive definite matrix factorization was used to identify potential sources of PM2.5, and the backward trajectory model was used to calculate the contribution of the long-distance transmission of air particles to the Baoshan area. It was found that in the wet season, most of the air masses come from the Indian Ocean and Myanmar. In the dry season, the air mass mainly comes from the China and Myanmar border area. The average concentration of PM2.5 in the wet and dry seasons was 23.17 ± 12.23 μg/m3. The daily mean value of OC/EC indicated that the measured SOC content was generated by the photochemical processes active during the sampling days. However, elements from anthropogenic sources (Na, Mg, Al, Si, P, K, Ca, Ti, Fe, Cu, Zn, Sb, Ba, and Pb) accounted for 99.51% and 99.40% of the total inorganic elements in the wet season and dry season, respectively. Finally, source apportionment showed that SIA, dust, industry, biomass burning, motor vehicle emissions, and copper smelting emissions constituted the major contributions of PM2.5 in Baoshan. Using combined data from three measurement sites provides a focus on the common sources affecting all locations.

Statistical Models For Sunshine Duration Related To Precipitation And Relative Humidity

Energy usage leads to environmental problems especially climate change and air pollution. In urban areas, extensive consumption of fossil energy sources deteriorates urban air quality and causes health problems such as asthma and respiratory diseases. The usage of renewable energy sources mainly solar energy instead of fossil energy sources provide the healthier and cleaner environment. Some statistical approaches have been used to predict the solar radiation for many years. The formula which is named as Angström-Prescott is widely used for the estimation. This approach uses the value of relative sunshine duration which is computed by using the daily measurement of sunshine duration and the daylength. Sunshine duration has been measured at meteorological stations for a long time. But in some cases such as remote areas or non-exist stations, sunshine duration is forecasted by using statistical methods. In atmospheric environment, sunshine duration is affected from other climate parameters such as cloud cover, wind speed, relative humidity, precipitation, air temperature, pressure. This paper offers to gain the relationships for sunshine duration via precipitation and relative humidity. To construct the statistical models, cloud cover was entered the models firstly because of its association with sunshine duration. Many studies were shown that sunshine duration was highly correlated to the cloud cover. The observed daily mean values of sunshine duration and climate elements were the data of Samsun meteorological station measured by Turkish State Meteorological Service. To acquire the statistical models for sunshine duration, data was arranged as monthly mean values and then linear regression analysis method was operated. Also the graphs of time series of climate variables were visually created for a clear interpretation. According to the findings, sunshine duration can be estimated bu using statistical models over cloud cover, precipitation and relative humidity. The contributions of precipitation and relative humidity change for different time scales.

Relationship Between Exposure to Sulphur Dioxide Air Pollution, White Cell Inflammatory Biomarkers and Enzymatic Infarct Size in Patients With ST-segment Elevation Acute Coronary Syndromes.

Aims: To analyse the relationship among air pollutants, markers of inflammation and infarct size in patients with acute coronary syndrome (ACS). Methods: This was a prospective analysis of consecutive patients admitted to hospital because of ACS. Cardiac biomarkers were drawn. The daily mean values of the air pollutants from the day before until 7 days before admission were analysed. The study population was stratified according to infarct size, based on median peak troponin value. Results: Patients were divided into two groups of 108 subjects each, according to median peak troponin value. Patients with extensive MIs had a higher neutrophil:lymphocyte ratio and leukocyte and neutrophil counts than patients with smaller MIs. In addition, they were exposed to higher concentrations of sulphur dioxide (9.7 ± 4.1 versus 8.4 ± 3.1 μg/m3; p=0.009) and lower concentrations of ozone (33.8 ± 13.7 versus 38.6 ± 14.5 μg/m3; p=0.014). Multivariate analysis showed that sulphur dioxide levels (OR 1.12; 95% CI [1.031–1.21]; p=0.007) and neutrophil/lymphocyte ratio (OR 1.08; 95% CI [1.011–1.17]; p=0.024) were independent predictors of infarct size. Conclusion: Patients with extensive MIs had higher white cell inflammatory levels and had been exposed to higher sulphur dioxide concentrations in the ambient air.

Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown.

The megacities experience poor air quality frequently due to stronger anthropogenic emissions. India had one of the longest lockdowns in 2020 to curb the spread of COVID-19, leading to reductions in the emissions from anthropogenic activities. In this article, the frequency distributions of different pollutants have been analysed over two densely populated megacities: Delhi (28.70° N; 77.10° E) and Kolkata (22.57° N; 88.36° E). In Delhi, the percentage of days with PM2.5 levels exceeding the National Ambient Air Quality Standards (NAAQS) between 25 March and 17 June dropped from 98% in 2019 to 61% in 2020. The lockdown phase 1 brought down the PM10 (particulate matter having an aerodynamic diameter ≤ 10 μm) levels below the daily NAAQS limit over Delhi and Kolkata. However, PM10 exceeded the limit of 100 μgm−3 during phases 2–5 of lockdown over Delhi due to lower temperature, weaker winds, increased relative humidity and commencement of limited traffic movement. The PM2.5 levels exhibit a regressive trend in the highest range from the year 2019 to 2020 in Delhi. The daily mean value for PM2.5 concentrations dropped from 85–90 μgm−3 to 40–45 μgm−3 bin, whereas the PM10 levels witnessed a reduction from 160–180 μgm−3 to 100–120 μgm−3 bin due to the lockdown. Kolkata also experienced a shift in the peak of PM10 distribution from 80–100 μgm−3 in 2019 to 20–40 μgm−3 during the lockdown. The PM2.5 levels in peak frequency distribution were recorded in the 35–40 μgm−3 bin in 2019 which dropped to 15–20 μgm−3 in 2020. In line with particulate matter, other primary gaseous pollutants (NOx, CO, SO2, NH3) also showed decline. However, changes in O3 showed mixed trends with enhancements in some of the phases and reductions in other phases. In contrast to daily mean O3, 8-h maximum O3 showed a reduction over Delhi during lockdown phases except for phase 3. Interestingly, the time of daily maximum was observed to be delayed by ~ 2 h over Delhi (from 1300 to 1500 h) and ~ 1 h over Kolkata (from 1300 to 1400 h) almost coinciding with the time of maximum temperature, highlighting the role of meteorology versus precursors. Emission reductions weakened the chemical sink of O3 leading to enhancement (120%; 11 ppbv) in night-time O3 over Delhi during phases 1–3.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-021-16874-z.

Evaluation of Production and Economic Performance of Farmed Carp Using Small Lake-Commercial Fish Farms System in Southeastern Kazakhstan.

The objective of changing the simple exploitation of fish stocks to highly efficient fish farms in lakes and reservoirs is to improve the productivity of inland freshwater fish. The small- and medium-sized lakes can be used to increase the production of farmed fish with lake management. Therefore, this study proposed to investigate the production and economic efficiency of carp in lake commercial fish farms. In this investigation, the results of carp farming experiments in fish farms in small lake commercial fish farms (LCFF) are evaluated using advanced methods and techniques. The research was carried out based on the Voroshilovsky reservoir, which operated in the LCFF mode. The farm had hatchery and carp fry ponds for expanding fingerlings based on the "Scientific and production center of fishery" LLP from 2019 to 2020. This study was performed on different types of common carp and herbivorous fish (grass and silver carp), and sexual products were collected in fried ponds and the Voroshilovsky reservoir. The absolute growth gain of common carp, silver carp, and grass carp were 301.00, 300.40, and 577.00 grams, respectively, and their mean daily weight gain values were 2.50, 2.50, and 4.80 grams. Common carp recorded the highest level of planned fish productivity (169.30 kg/ha), and the lowest level of this trait was grass carp (43.50 kg/ha). Data of mean weight and body length of common carp, grass carp, and silver carp fishes showed a variation of 4.55 kg and 56.25 cm, 6.06 kg and 75.50 cm, as well as 6.30 Kg and 75.05 cm, respectively. This difference can be justified according to the variance of fish length, which on average, 80 grams of weight is obtained per centimeter of fish length. The economic efficiency of carp was calculated, and the net profit was determined at more than 50% of total income. According to the net profit indicator, due to the implementation of a part of the fingerlings, the carp reared in the pond area; as a result, this method is profitable and accounts for 104% of the total planned economic profit. Therefore, fish production from aquaculture can rise to 10 times to maintain high-quality food security and other essential nutrients, provide job opportunities, and cash income to help job-seeking youth.

A Model for the Relationship between Rainfall, GNSS-Derived Integrated Water Vapour, and CAPE in the Eastern Central Andes

Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.

A high-spatial-resolution dataset of human thermal stress indices over South and East Asia

Thermal stress poses a major public health threat in a warming world, especially to disadvantaged communities. At the population group level, human thermal stress is heavily affected by landscape heterogeneities such as terrain, surface water, and vegetation. High-spatial-resolution thermal-stress indices, containing more detailed spatial information, are greatly needed to characterize the spatial pattern of thermal stress to enable a better understanding of its impacts on public health, tourism, and study and work performance. Here, we present a 0.1° × 0.1° gridded dataset of multiple thermal stress indices derived from the newly available ECMWF ERA5-Land and ERA5 reanalysis products over South and East Asia from 1981 to 2019. This high-spatial-resolution database of human thermal stress indices over South and East Asia (HiTiSEA), which contains the daily mean, maximum, and minimum values of UTCI, MRT, and eight other widely adopted indices, is suitable for both indoor and outdoor applications and allows researchers and practitioners to investigate the spatial and temporal evolution of human thermal stress and its impacts on densely populated regions over South and East Asia at a finer scale.

FTIR Measurements of Greenhouse Gases over Thessaloniki, Greece in the Framework of COCCON and Comparison with S5P/TROPOMI Observations

In this work, column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4) and carbon monoxide (XCO) are presented for the first time at a mid-latitude urban station, Thessaloniki, Greece, using the Bruker EM27/SUN ground-based low-resolution Fourier Transform spectrometer operated according to the requirements of the Collaborative Carbon Column Observing Network (COCCON). Two years of measurements are presented and examined for seasonal variability. The observed XCO2 levels show the expected seasonal cycle (spring maximum, late summer minimum) with a peak-to-peak amplitude of 12 ppm, with maximum values reported for winter 2021 exceeding 416 ppm. The XCH4 values are shown to increase in the second half of the year, with autumn showing the highest mean value of 1.878 ± 0.01 ppm. The XCO levels, following anthropogenic sources, show high winter and low summer values, exhibiting a rise again in August and September with a maximum value of 114 ± 3 ppb and a minimum in summer 2020 of 76 ± 3 ppb. Additionally, methane and carbon monoxide products obtained from the TROPOspheric Monitoring Instrument (TROPOMI), Sentinel-5P space borne sensor, are compared with the ground-based measurements. We report a good agreement between products. The relative mean bias for methane and carbon monoxide are −0.073 ± 0.647% and 3.064 ± 5.566%, respectively. Furthermore, a 15-day running average is subtracted from the original daily mean values to provide ΔXCO2, ΔXCO and ΔXCH4 residuals, so as to identify local sources at a synoptic scale. ΔXCO and ΔXCO2 show the best correlation in the winter (R2 = 0.898, slope = 0.007) season due to anthropogenic emissions in this period of the year (combustion of fossil fuels or industrial activities), while in summer no correlation is found. ΔXCO and ΔXCH4 variations are similar through both years of measurements and have a very good correlation in all seasons including winter (R2 = 0.804, slope = 1.209). The investigation of the X-gases comparison is of primary importance in order to identify local sources and quantify the impact of these trace gases to the deregulation of earth-climate system balance.

A mean-sea-level pressure time series for Trieste, Italy (1841–2018)

Abstract. A time series of mean-sea-level pressure was built from observations performed in Trieste from 1 January 1841 to 31 December 2018. Original historical documents provided information on the instruments and on the observation sites. Mercury barometers have always been available. Until 1877 they represented the only instruments in operation, while from 1878 onwards barograph records became available. The time series consists of mean daily values that were computed from 24-hourly data, when possible, or otherwise adjusted to 24 h means on the basis of climatological daily pressure cycles. The time series was homogenized on the basis of the available metadata, reducing pressure to 0 ∘C and to mean sea level. Basic quality checks were applied, including the comparison with pressure time series from nearby stations. As a result, the data prior to 1865 turned out to be suspect. A mean-sea-level pressure trend of 0.5 ± 0.2 hPa per century was estimated for the 1865–2018 period. The data are available through PANGAEA (https://doi.org/10.1594/PANGAEA.926896; Raicich and Colucci, 2021).